CN117172399A - Automatic wire laying track planning method based on heuristic algorithm - Google Patents
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Abstract
The application belongs to the technical field of composite material manufacturing, and particularly relates to an automatic wire laying track planning method based on a heuristic algorithm, which comprises the following steps: reconstructing an STL file, constructing a mapping relation between vertexes and adjacent vertexes by a design algorithm, and recording corresponding boundary information; calculating the state of an initial wire laying point, and selecting a vertex corresponding to an optimal path under the condition of minimum evaluation function value; and adopting a backtracking algorithm for the vertex of the whole wire laying path to realize wire laying path planning. The application greatly reduces the accumulated error in the whole path planning, thereby improving the calculation efficiency of the whole path planning, utilizing the dictionary to store the vertex information in the file and the vertex neighbor vertex and boundary information, defining the heuristic function, and utilizing the heuristic algorithm to efficiently solve the wire laying track, thereby obtaining the performance superior to other technologies in the aspects of optimizing the path and improving the path generation efficiency.
Description
Technical Field
The application belongs to the technical field of composite material manufacturing, and particularly relates to an automatic wire laying track planning method based on a heuristic algorithm.
Background
The automatic wire laying technology (Automated Fiber Placement, AFP) is that under the control of a multi-coordinate automatic wire laying machine, a wire laying head bundles a plurality of presoaked tows into a belt under a press roller through the functions of unreeling, guiding, conveying and the like, and automatically lays according to a planned track. The path planning in the automatic wire laying technology of the composite material is the core content and key of the automatic wire laying technology, and the track planning mode, coverage control and laying boundary treatment directly influence the laying forming process and the performance of the components. Automatic wire lay-up path planning is of great importance to improve the productivity of the composite material and to reduce the manufacturing costs.
However, the research on the calculation method of the wire laying path planning in foreign countries is relatively mature, and the published algorithm related to the method is extremely limited. Shirinzade et al propose a wire laying path planning algorithm for open surfaces. The method utilizes the intersection of a curved surface and a plane to construct an initial reference path, and then uses the reference path as a reference to carry out parallel equidistant in the direction perpendicular to the tangential direction of the reference path so as to realize the full-spread of the whole open curved surface. Parnas et al use bicubic Bezier surfaces and curves to represent the surface and fiber paths, respectively, and use sequential quadratic programming to optimize the lay path with the coordinates of spline control points as variables. Waldhart teaches a method of covering a curved surface with tows that, for a known initial center reference trajectory, finds a direction perpendicular to its tangential vector, and then offsets a distance such that the family of trajectories uniformly covers the complete curved surface. The algorithm solving process is mainly based on differential geometry, spline curves and other related knowledge, and the processing efficiency is low due to the large calculated amount. In view of the advantages of mesh surfaces in complex surface representation and finite element analysis, lewis et al first put forward the concept of "natural path" and apply it to trajectory planning for automatic tape laying. Bruyneel et al propose an improved discrete finite element based fast tracking algorithm that calculates the local fiber direction of each grid cell and then constructs equidistant parallel trajectories on the grid surface. The algorithm is only applicable to mesh surfaces with simple open edges, and does not consider geodesic curvature of the trajectory. Xu et al assume that the mandrel surface can be expanded into a planar mesh and parallel equidistant paths are planned on the planar mesh and then mapped to the initial mesh surface. The method is only applicable to a deployable surface, an approximately deployable surface or a single curvature surface. When the curvature change is large, the accumulated error is large, the calculation result is high in geometry, and the calculation amount is large, so that the efficiency is low.
Disclosure of Invention
In order to solve the problems, the application provides an automatic wire laying track planning method based on a heuristic algorithm.
In order to achieve the above object, the present application provides the following technical solutions:
an automatic wire laying track planning method based on a heuristic algorithm comprises the following steps:
step1, reconstructing an STL file, constructing a mapping relation between vertexes and adjacent vertexes by a design algorithm, and recording corresponding boundary information;
step2, calculating the state of an initial wire laying point, and selecting a vertex corresponding to the optimal path under the condition of minimum evaluation function value; and adopting a backtracking algorithm for the vertex of the whole wire laying path to realize wire laying path planning.
Further, the Step1 includes:
step 1.1: first initializing a dictionaryN vertices +.>Is>；
Step 1.2: traversing all vertexes to store the point and boundary information thereof, and acquiring information of neighbor nodes around each vertex through each vertexAnd acquiring adjacent points of each vertex as important information for judging whether the adjacent points are boundary points or not by reading and numbering the vertexes of all triangular surfaces in the STL file and utilizing a set deduplication mode.
Further, the Step2 includes:
step 2.1: reading the preprocessed STL file;
step 2.2: constructing heuristic functionsThe method is used for approximately solving the geodesic line, so that the laying point to be passed by the next optimal path can be conveniently searched; redundancy is removed for the STL file, and vertex information in the file, neighbor vertexes of all vertexes and boundary information are stored by utilizing a dictionary;
the saidRepresenting the actual cost of the deposit path from the initial deposit point to the expanded deposit point, < >>Representing the estimated cost of the expanded laydown point to the target laydown point, < >>Representing the total cost of the initial placement point to the target placement point; x represents all possible deposit points;
step 2.3: initialization ofOpenListA table (for storing all generated and unexpanded filament placement points),CloseListTable (record accessed wire laying points) and path backtracking tableTraceList(recording complete wire laying path), initial laying pointPut intoOpenListA table in whichOpenListWatch(s)CloseListThe attributes of the table include the coordinates of the deposit points, the direction of the deposit points and +.>Value sum->A value;
step 2.4: solving in an OpenList table using heuristic functionsMinimum of the values +.>Finding out the corresponding laying point +.>The solution formula is as follows:
；
wherein the method comprises the steps ofFor the neighboring node of the current deposit point, +.>Corresponding to all neighbor nodes of the current laying point in the solving process of the laying path>Value of->To solve the next deposit point, all neighboring nodes are passed through +.>The node with the smallest value is taken as the solution of the next laying point;
step 2.5: lay-up points solved in step 2.4Acquiring neighbor vertexes of the dictionary established in the first stage, and laying points +.>Adding neighbor vertex information as an expanded laying pointOpenListIn the table, the laying points->Put intoCloseListIn the table;
step 2.6: judgingOpenListIf the table is empty, the process goes to step 2.7, if the idle running is not performed, the process goes to the step 2.4;
step 2.7: for a pair ofCloseListCarrying out path backtracking on the laying points in the table, and firstly obtaining a target laying pointAccording to the coordinate valuesCloseListThe corresponding +.>Value sum->The value backtracking out the last deposit point +.>By such a push back the optimal laying path +.>Wherein->For the initial deposit point>To solve for the resulting second deposit point.
Still further, in step 2.2Representing the actual cost of the deposit path from the initial deposit point to the expanded deposit point, < >>The application adopts the Euclidean distance to calculate the actual cost and the estimated cost of each laying path, including the distance calculation of three-dimensional space coordinates, and in order to reduce the influence of curvature on the cost result, the application uses the three-dimensional space to calculate the estimated cost of the expanded laying point to the target laying pointzThe coordinate estimation cost is unified to zero, wherein +.>Three-dimensional space seat representing current laying pointMark (I) of->Neighbor nodes representing the current placement point, i.e. expandable nodes,>the three-dimensional space coordinates of the target laying point are represented by the following formula:
the beneficial effects of the application are as follows:
1. according to the application, the STL file is preprocessed by using the python programming language, vertex information in a corresponding curved surface and information of adjacent vertexes of each vertex are stored in the dictionary, a foundation is laid for the establishment of a subsequent simulation model and wire laying path planning, and then the solution of the triangular piece geodesic wire is approximated by using a heuristic algorithm. Therefore, the application overcomes the defects of large calculated amount and need to solve the second-order or more ordinary differential equation of the traditional algorithm, greatly reduces the accumulated error in the whole path planning, and improves the calculation efficiency of the whole path planning.
2. The application removes redundancy for STL files, stores vertex information and adjacent vertex and boundary information of each vertex in the files by using a dictionary, defines a heuristic function by using a heuristic algorithm-based wire laying track optimization method, and further measures selection of next-step wire laying points by using Euclidean distance in the heuristic algorithm, thereby obtaining performance superior to other technologies in the aspects of path optimization and path generation efficiency increase.
Drawings
FIG. 1 is a flowchart showing the implementation of Step2 wire laying path planning according to the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are intended to explain the present application rather than to limit the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The following describes a specific implementation of the present application with reference to the drawings and examples, to which the present application is not limited.
Example 1
The automatic wire laying track planning method based on the heuristic algorithm comprises the following steps:
step1, reconstructing an STL file, constructing a mapping relation between vertexes and adjacent vertexes by a design algorithm, and recording corresponding boundary information;
step2, calculating the state of an initial wire laying point, and selecting a vertex corresponding to the optimal path under the condition of minimum evaluation function value; and adopting a backtracking algorithm for the vertex of the whole wire laying path to realize wire laying path planning.
The Step1 includes:
step 1.1: first initializing a dictionaryReading vertex set +.>；
Step 1.2: traversing all vertexes to store the point and boundary information thereof, and acquiring information of neighbor nodes around each vertex through each vertexObtaining each vertex by reading and numbering the vertices of all triangular surfaces in the STL file and adopting a collective deduplication modeAs important information for judging whether or not it is a boundary point.
As shown in fig. 1, step2 includes:
step 2.1: reading the preprocessed STL file;
step 2.2: constructing heuristic functionsThe method is used for approximately solving the geodesic line, so that the laying point to be passed by the next optimal path can be conveniently searched; said->Representing the actual cost of the deposit path from the initial deposit point to the expanded deposit point, < >>Representing the estimated cost of the expanded deposit point to the target deposit point,/->Representing the total cost of the initial deposit point to the target deposit point, x representing all possible deposit points; the application adopts the Euclidean distance to calculate the actual cost and the estimated cost of each laying path, including the distance calculation of three-dimensional space coordinates, and in order to reduce the influence of curvature on the cost result, the application uses the three-dimensional spacezThe coordinate estimation cost is unified to zero, wherein +.>Representing the three-dimensional space coordinates of the current deposit point,neighbor nodes representing the current placement point, i.e. expandable nodes,>the three-dimensional space coordinates of the target laying point are represented by the following formula:
step 2.3: initialization ofOpenListA table (for storing all generated and unexpanded filament placement points),CloseListTable (record accessed wire laying points) and path backtracking tableTraceList(recording complete wire laying path), initial laying pointPut intoOpenListA table in whichOpenListWatch(s)CloseListThe attributes of the table include the coordinates of the deposit points, the direction of the deposit points and +.>Value sum->A value;
step 2.4: solving in an OpenList table using heuristic functionsMinimum of the values +.>Finding out the corresponding laying point +.>The solution formula is as follows:
；
wherein the method comprises the steps ofFor the neighboring node of the current deposit point, +.>Corresponding to all neighbor nodes of the current laying point in the solving process of the laying path>Value of->To solve the next deposit point, all neighboring nodes are passed through +.>The node with the smallest value is taken as the solution of the next laying point;
step 2.5: lay-up points solved in step 2.4Acquiring neighbor vertexes of the dictionary established in the first stage, and laying points +.>Adding neighbor vertex information as an expanded laying pointOpenListIn the table, the laying points->Put intoCloseListIn the table;
step 2.6: judgingOpenListIf the table is empty, turning to step 2.7, and if not, turning to step 2.4;
step 2.7: for a pair ofCloseListCarrying out path backtracking on the laying points in the table, and firstly obtaining a target laying pointAccording to the coordinate valuesCloseListThe corresponding +.>Value sum->The value backtracking out the last deposit point +.>By such a push back the optimal laying path +.>Wherein->For the initial deposit point>To solve for the resulting second deposit point.
Example 2
Referring to fig. 1, a first stage: STL file
STL (Stereo Lithography) the file format is an interface standard for interfacing 3D model methods proposed by the company 3D systsm in the united states. STL files have the characteristics of standard format and small data volume, are currently accepted by industry as standard file formats in the field of rapid prototyping, and are widely applied to various aspects, such as three-dimensional modeling reconstruction, finite element analysis, medical image visualization, cultural relic restoration and the like. The STL file is composed of a plurality of triangle patch definitions, each triangle patch definition including three-dimensional coordinates of each of the triangle's points and normal vectors of the triangle patches. STL files include 2 types: text files (ASCII format) and BINARY files (BINARY), herein STL files in ASCII format, are employed to facilitate reading of the files. The STL file preprocessing process is as follows:
first initializing a dictionaryReading node set +.>WhereinKeyEach of the vertex coordinates is represented as such,Valueis in combination withKeyCoordinates of each corresponding adjacent vertex; secondly, the points and the boundary information thereof are stored by traversing all the vertexes, and the information of the neighboring nodes around the vertexes can be acquired by each vertex>And finally, acquiring the adjacent points of each vertex as important information for judging whether the adjacent points are boundary points or not by reading the vertexes of all triangular surfaces in the STL file and numbering the vertexes and utilizing a set deduplication mode.
And a second stage: heuristic algorithm wire laying path solving
Therefore, the method utilizes the evaluation function in the heuristic algorithm to solve the distance between the initial laying point and the neighbor laying point in the triangular plate to approach the geodesic line so as to achieve the effect of optimizing the path. The specific algorithm comprises the following steps:
step (1): reading the STL file and preprocessing;
step (2): constructing heuristic functionsThe method is used for approximately solving the geodesic line, so that the laying point to be passed by the next optimal path can be conveniently searched;
the saidRepresenting the actual cost of the deposit path from the initial deposit point to the expanded deposit point, < >>Representing the estimated cost of the expanded deposit point to the target deposit point,/->Representing the total cost of the initial placement point to the target placement point; x represents all possible deposit points;
step (3): initialization ofOpenListA table (for storing all generated and unexpanded filament placement points),CloseListTable (record accessed wire laying points) and path backtracking tableTraceList(recording complete wire laying path), initial laying pointPut intoOpenListA table in whichOpenListWatch(s)CloseListThe attributes of the table include the coordinates of the deposit points, the direction of the deposit points and +.>Value sum->A value;
step (4): solving in an OpenList table using heuristic functionsMinimum of the values +.>Finding out the corresponding laying point +.>The solution formula is as follows:
；
wherein the method comprises the steps ofFor the neighboring node of the current deposit point, +.>Corresponding to all neighbor nodes of the current laying point in the solving process of the laying path>Value of->To solve the next deposit point, all neighboring nodes are passed through +.>The node with the smallest value is taken as the solution of the next laying point;
step (5): lay-up points solved in step (4)Acquiring neighbor vertexes of the dictionary established in the first stage, and laying points +.>Adding neighbor vertex information as an expanded laying pointOpenListIn the table, the laying points->Put intoCloseListIn the table;
step (6): judgingOpenListIf the table is empty, turning to the step (7), and if the table is not empty, turning to the step (4);
step (7): for a pair ofCloseListCarrying out path backtracking on the laying points in the table, and firstly obtaining a target laying pointAccording to the coordinate valuesCloseListThe corresponding +.>Value sum->The value backtracking out the last deposit point +.>By such a push back the optimal laying path +.>Wherein->For the initial deposit point>To solve for the resulting second deposit point.
The application adopts the Euclidean distance to calculate the actual cost and the estimated cost of each laying path, including the distance calculation of three-dimensional space coordinates, and in order to reduce the influence of curvature on the cost result, the application uses the three-dimensional spacezThe coordinate estimation cost is unified to zero, whereinRepresenting the three-dimensional space coordinates of the current laying point, +.>Neighbor nodes representing the current placement point, i.e. expandable nodes,>the three-dimensional space coordinates of the target laying point are represented by the following formula:
in the application, the STL file is preprocessed by using the python programming language, vertex information in a corresponding curved surface and information of adjacent vertexes of each vertex are stored in the dictionary, a foundation is laid for the establishment of a subsequent simulation model and wire laying path planning, and then the solution of the triangular plate geodesic wire is approximated by using a heuristic algorithm. Therefore, the method overcomes the defects of large calculated amount and need to solve the second-order or more ordinary differential equations of the traditional algorithm, greatly reduces the accumulated error in the overall path planning, and improves the calculation efficiency of the overall path planning; the method and the device remove redundancy of the STL file, store vertex information and vertex neighbor vertices and boundary information in the file by utilizing a dictionary, define a heuristic function by using a heuristic algorithm-based wire laying track optimization method, efficiently solve the wire laying track by utilizing the heuristic algorithm, and further measure selection of next-step wire laying points by utilizing the Euclidean distance, thereby obtaining performance superior to other technologies in the aspects of path optimization and path generation efficiency increase.
The above embodiments are only for illustrating the technical solution of the present application, and are not intended to limit the present application, and various modifications and variations can be provided to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (7)
1. An automatic wire laying track planning method based on a heuristic algorithm is characterized by comprising the following steps of: the method comprises the following steps:
step1, reconstructing an STL file, constructing a mapping relation between vertexes and adjacent vertexes by a design algorithm, and recording corresponding boundary information;
step2, calculating the state of an initial wire laying point, and selecting a vertex corresponding to the optimal path under the condition of minimum evaluation function value; and adopting a backtracking algorithm for the vertex of the whole wire laying path to realize wire laying path planning.
2. The heuristic algorithm-based automatic wire laying track planning method as claimed in claim 1, wherein the method comprises the following steps: the Step1 includes:
step 1.1: first initializing a dictionaryN vertices +.>Is>；
Step 1.2: traversing all vertexes to store the point and boundary information thereof, and acquiring information of neighbor nodes around each vertex through each vertexAnd acquiring adjacent points of each vertex as important information for judging whether the adjacent points are boundary points or not by reading and numbering the vertexes of all triangular surfaces in the STL file and utilizing a set deduplication mode.
3. The automatic wire laying track planning method based on heuristic algorithm as claimed in claim 2, wherein the method comprises the following steps: the Step2 includes:
step 2.1: reading the preprocessed STL file;
step 2.2: constructing heuristic functionsThe method is used for approximately solving the geodesic line, so that the laying point to be passed by the next optimal path can be conveniently searched; redundancy is removed for the STL file, and vertex information in the file, neighbor vertexes of all vertexes and boundary information are stored by utilizing a dictionary;
the saidRepresenting the actual cost of the deposit path from the initial deposit point to the expanded deposit point, < >>Representing the estimated cost of the expanded deposit point to the target deposit point,/->Representing the total cost of the initial placement point to the target placement point; x represents all possible deposit points;
step 2.3: initialization ofOpenListA watch (watch),CloseListTable and path trace-back tableTraceListWill initially lay down the dotsPut intoOpenListA table in whichOpenListWatch(s)CloseListThe attributes of the table include the coordinates of the deposit points, the direction of the deposit points and +.>Value sum->A value;
step 2.4: solving in an OpenList table using heuristic functionsMinimum of the values +.>Finding out the corresponding laying point +.>The solution formula is as follows:
；
wherein the method comprises the steps ofFor the neighboring node of the current deposit point, +.>Corresponding to all neighbor nodes of the current laying point in the solving process of the laying path>Value of->To solve the next deposit point, all neighboring nodes are passed through +.>The node with the smallest value is taken as the solution of the next laying point;
step 2.5: lay-up points solved in step 2.4Acquiring neighbor vertexes of the dictionary established in the first stage, and laying points +.>Adding neighbor vertex information as an expanded laying pointOpenListIn the table of the present application,lay-on points->Put intoCloseListIn the table;
step 2.6: judgingOpenListIf the table is empty, turning to step 2.7, and if not, turning to step 2.4;
step 2.7: for a pair ofCloseListCarrying out path backtracking on the laying points in the table, and firstly obtaining a target laying pointAccording to the coordinate valuesCloseListThe corresponding +.>Value sum->The value backtracking out the last deposit point +.>By such a push back the optimal laying path +.>Wherein->For the initial deposit point>To solve for the resulting second deposit point.
4. A heuristic algorithm-based automatic wire laying trajectory planning method according to claim 3, characterized in that: in the step 2.2, the three-dimensional space is formedzThe coordinate estimation cost is unified to zero, whereinRepresenting the three-dimensional space coordinates of the current laying point, +.>A neighboring node, i.e. an expandable node,the three-dimensional space coordinates of the target laying point are represented by the following formula:
。
5. a heuristic algorithm-based automatic wire laying trajectory planning method according to claim 3, characterized in that:OpenListthe table is used to hold all the generated and unexpanded wire laying points.
6. A heuristic algorithm-based automatic wire laying trajectory planning method according to claim 3, characterized in that:CloseListthe table is used to record accessed laying points.
7. A heuristic algorithm-based automatic wire laying trajectory planning method according to claim 3, characterized in that: path backtracking tableTraceListFor recording the complete wire laying path.
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